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Jackson C. Kirkman-Brown

dblp:164/7873 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
0000-0003-2833-8970ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics › visual encoding
glyph-based visualization
0.212015
Glyph-Based Video Visualization for Semen Analysis · IEEE Trans. Vis. Comput. Graph. 2015
Visualization and visual analytics
video visualization
0.212015
Glyph-Based Video Visualization for Semen Analysis · IEEE Trans. Vis. Comput. Graph. 2015
Medical and health informatics
sperm analysis
0.112015
Glyph-Based Video Visualization for Semen Analysis · IEEE Trans. Vis. Comput. Graph. 2015

Methods — techniques the papers use, named apart from their topics

spatio-temporal motion summarization · 0.4glyph encoding · 0.4
YearPublicationVenuePosition
2015 Glyph-Based Video Visualization for Semen Analysis
abstract
The existing efforts in computer assisted semen analysis have been focused on high speed imaging and automated image analysis of sperm motility. This results in a large amount of data, and it is extremely challenging for both clinical scientists and researchers to interpret, compare and correlate the multidimensional and time-varying measurements captured from video data. In this work, we use glyphs to encode a collection of numerical measurements taken at a regular interval and to summarize spatio-temporal motion characteristics using static visual representations. The design of the glyphs addresses the needs for (a) encoding some 20 variables using separable visual channels, (b) supporting scientific observation of the interrelationships between different measurements and comparison between different sperm cells and their flagella, and (c) facilitating the learning of the encoding scheme by making use of appropriate visual abstractions and metaphors. As a case study, we focus this work on video visualization for computer-aided semen analysis, which has a broad impact on both biological sciences and medical healthcare. We demonstrate that glyph-based visualization can serve as a means of external memorization of video data as well as an overview of a large set of spatiotemporal measurements. It enables domain scientists to make scientific observation in a cost-effective manner by reducing the burden of viewing videos repeatedly, while providing them with a new visual representation for conveying semen statistics.
Brian Duffy, Jeyan Thiyagalingam, Simon J. Walton, David J. Smith, Anne E. Trefethen, Jackson C. Kirkman-Brown, Eamonn A. Gaffney, Min Chen 0001
IEEE Trans. Vis. Comput. Graph.6